Tata Consultancy Services (TCS) has done the Indian information technology (IT) industry a service by choosing clarity over rhetoric on artificial intelligence (AI). At its analyst day last week, the country’s largest software exporter not only outlined an AI-first strategy but, crucially, put a number to it. The disclosure that TCS has reached an annualised $1.5 billion run rate from AI-related services, growing more than 16% sequentially, is among the first serious attempts by a large Indian IT firm to separate signal from noise in a space increasingly prone to exaggeration.
Why TCS Disclosed the $1.5 Billion Metric
The timing is significant. AI is no longer a discrete technology layer or a fashionable add-on; it is rapidly becoming synonymous with enterprise technology itself. That reality was underscored a day later when Accenture reported its quarterly results. The global consulting major said its advanced AI bookings had nearly doubled year-on-year to $2.2 billion and AI revenues had climbed to $1.1 billion, up 120%. Yet it also announced it would stop reporting AI as a separate line item, arguing that AI is now embedded across most projects—from data modernisation to core operations—making segregation increasingly meaningless.
Together, the two disclosures capture where the industry stands today. TCS’s decision to spell out AI revenues reflects a phase where investors, clients, and employees still need visibility on how quickly AI is moving from pilots to monetisation. Investors want clarity on revenue run rates and margins, not anecdotal success stories. Clients want proof that AI deployments will deliver measurable outcomes, not just dashboards. Accenture’s move points to the end state: AI as the default mode of delivery rather than a distinct revenue stream. Outside TCS, most large Indian IT firms continue to speak in generalities. Infosys tracks AI-linked revenue internally but does not disclose it. Wipro, HCLTech, LTIMindtree, and Tech Mahindra emphasise platforms, deal wins or productivity gains, while avoiding a consolidated monetary figure for AI. The reluctance is understandable. AI revenues remain intertwined with cloud migration, digital engineering, and application modernisation, making clean attribution difficult. There is also the risk of setting expectations too early in a fast-evolving market. Yet, as TCS has shown, even a directional number—anchored in engagement scale and growth rates—helps ground the conversation in facts rather than hype.
End of Segregation
The upcoming third-quarter earnings season offers the rest of the sector an opportunity to follow suit. Even limited, standardised disclosures would help investors distinguish between companies that are genuinely scaling AI and those still experimenting at the margins. More importantly, it would signal confidence in execution at a time when global clients are beginning to ask tougher questions about returns on AI spending. TCS’s credibility is further strengthened by its moves beyond services into enabling infrastructure. Its plans to invest, directly and through partnerships, in AI-ready data-centre capacity in India reflect a longer-term view of where value will accrue. As data localisation, energy efficiency, and sovereign compute become strategic issues, the ability to pair infrastructure with services could differentiate Indian firms from global peers that rely heavily on hyperscalers. The broader message for the industry is clear: AI is no side bet. Indian IT companies still benefit from scale, talent depth, and client proximity that few geographies can match. But these advantages will erode if caution persists while global competitors normalise AI-led delivery. TCS has set a benchmark. In a market where AI is becoming indistinguishable from technology itself, silence is no longer a neutral stance.